Full Stack ML Engineer
Full Stack ML Engineer
Posted on :
06-07-2025
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1 Vacancy
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Job Description
Description
Responsibilities
Qualifications
- Experience in SonarQube CICD Tekton terraform GCS GCP Looker Google cloud build cloud run Vertex AI Airflow TensorFlow etc.
- Experience in Train Build and Deploy ML DL Models
- Experience in HuggingFace Chainlit React
- Ability to understand technical functional non-functional security aspects of business requirements and delivering them end-to-end.
- Ability to adapt quickly with opensource products & tools to integrate with ML Platforms
- Building and deploying Models (Scikit learn TensorFlow PyTorch etc.)
- Developing and deploying On-Prem & Cloud environments
- Kubernetes Tekton OpenShift Terraform Vertex AI
- Experience in LLM models like PaLM GPT4 Mistral (open-source models)
- Work through the complete lifecycle of Gen AI model development from training and testing to deployment and performance monitoring.
- Developing and maintaining AI pipelines with multimodalities like text image audio etc.
- Have implemented in real-world Chat bots or conversational agents at scale handling different data sources.
- Experience in developing Image generation/translation tools using any of the latent diffusion models like stable diffusion Instruct pix2pix.
- Expertise in handlinglarge scale structured and unstructured data.
- Efficiently handled large-scale generative AI datasets and outputs.
- Familiarity in the use of Docker tools pipenv/conda/poetry env
- Comfort level in following Python project management best practices (use of logging pytests relative module importssphinx docsetc.)
- Familiarity in use of Github (clone fetch pull/push raising issues and PR etc.)
- High familiarity in the use of DL theory/practices in NLP applications
- Comfort level to code in Huggingface LangChain Chainlit Tensorflow and/or Pytorch Scikit-learn Numpy and Pandas
- Comfort level to use two/more of open source NLP modules like SpaCy TorchText farm-haystack and others
- Knowledge in fundamental text data processing (like use of regex token/word analysis spelling correction/noise reduction in text segmenting noisy unfamiliar sentences/phrases at right places deriving insights from clustering etc.)
- Have implemented in real-world BERT/or other transformer fine-tuned models (Seq classification NER or QA) from data preparation model creation and inference till deployment
- Use of GCP services like BigQuery Cloud function Cloud run Cloud Build VertexAI
- Good working knowledge on other open source packages to benchmark and derive summary
- Experience in using GPU/CPU of cloud and on-prem infrastructures
- Skillset to leverage cloud platform for Data Engineering Big Data and ML needs.
- Use of Dockers (experience in experimental docker features docker-compose etc.)
- Familiarity with orchestration tools such as airflow Kubeflow
- Experience in CI/CD infrastructure as code tools like terraform etc.
- Kubernetes or any other containerization tool with experience in Helm Argoworkflow etc.
- Ability to develop APIs with compliance ethical secure and safe AI tools.
- Good UI skills to visualize and build better applications using Gradio Dash Streamlit React Django etc.
- Deeper understanding of javascript css angular html etc. is a plus.
Responsibilities
- Design NLP/LLM/GenAI applications/products by following robust coding practices
- Explore SoTA models/techniques so that they can be applied for automotive industry usecases
- Conduct ML experiments to train/infer models; if need be build models that abide by memory & latency restrictions
- Deploy REST APIs or a minimalistic UI for NLP applications using Docker and Kubernetes tools
- Showcase NLP/LLM/GenAI applications in the best way possible to users through web frameworks (Dash Plotly Streamlit etc.)
- Converge multibots into super apps using LLMs with multimodalities
- Develop agentic workflow using Autogen Agentbuilder langgraph
- Build modular AI/ML products that could be consumed at scale.
Qualifications
- Bachelors or Masters Degree in Computer Science Engineering
- Have undergone any modern NLP/LLM courses or participation in open competitions are added advantage.
Employment Type
Full-Time
Key Skills
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